Watershed algorithms were originally developed as gray-level dedicated transformations. However, well known scalar watershed algorithms can be easily adapted to include multispectral information, producing color segmentations in agreement with the human perception. The multispectral watershed algorithm introduced in this paper includes the use of a vector gradient for calculating the Gradient Magnitude Image (GMI) and the choice of a uniform color space, such as the L*a*b*, for adapting the dissimilarity measures utilized in the merging stage. Experimental results are presented showing the advantages of the proposed adaptation method as well as advantages of combined homogeneity-edge integrity region merging criterion.